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As a lot of juvenile Muslims tend to be less engaged with their religion and the history of mosques in their community, this study was conducted to develop a series of digital content in the metaverse combined with participatory communication and learning with religious leader to enhance students' perception of community Mosque (Darun Naim, Thung Kru District, Thailand). The objectives of this research were to survey needs, to develop and assess the quality of the aforementioned series of digital content, to evaluate students' perception, and to measure students' satisfaction. Materials of this study included questionnaires and forms to survey needs, assess the quality of the digital content and media presentation, evaluate subjects perception, and measure their satisfaction. A total of 30 subjects who were students from Al-Bidayah Religious School, Thung Khru District, Bangkok and had been members of Young Muslim Association Ban Khru for at least 1 year were selected through purposive sampling. After questionnaire-based data collection, mean and standard deviation were used as a statistical tool for data analysis. The results of this study showed that the outcome of needs assessment was at a high level. The overall quality of the content and media presentation was at a good and very good level, respectively. The findings of the assessment of students' perception and satisfaction were at the highest level. In summary, the developed digital content in the metaverse combined with participatory communication and learning with religious leader was of high quality and can be implemented.

Given the lack of computational tools available for assessing second language (L2) production in Korean, this study introduces a novel automated tool called the Korean Syntactic Complexity Analyzer (KOSCA) for measuring syntactic complexity in L2 Korean production. As an open-source graphic user interface (GUI) developed in Python, KOSCA provides seven indices of syntactic complexity, including traditional and Korean-specific ones. Its validity was tested by investigating whether the syntactic complexity indices measured by it in L2 written and spoken production could explain the variability of L2 Korean learners' proficiency. The results of mixed-effects regression analyses showed that all seven indices significantly accounted for learner proficiency in Korean. Subsequent stepwise multiple regression analyses revealed that the syntactic complexity indices explained 56.0% of the total variance in proficiency for the written data and 54.4% for the spoken data. These findings underscore the validity of the syntactic complexity indices measured by KOSCA as reliable indicators of L2 Korean proficiency, which can serve as a valuable resource for researchers and educators in the field of L2 Korean learning and assessment.

Ray tracing is a computer graphics technique used to produce realistic visuals by physically simulating the behavior of light. Although this technique can be described straightforwardly, fully comprehending it might be challenging. It is typically taught in the classroom using the 2-D formats, such as paper or a blackboard. We propose using immersive environments for incrementing the understanding of ray tracing. We focus on improving the knowledge of the technique in experienced users, particularly Master of Computer Science students minoring in a computer-graphics-related area. We argue that exploring the ray tracing process in an immersive visualization environment can further improve the understanding of ray tracing acquired using conventional means. With that objective, this study starts by presenting RayTracerVR, a virtual reality prototype tool for learning the mechanisms of ray tracing. This tool can be used to visually explore and interact with the different aspects of the technique. It allows users to observe the progression of the rays throughout the sequential stages of the ray tracing process and analyze its corresponding computer pseudocode. The study includes user evaluation where RayTracerVR is employed to assess improvements in ray tracing understanding. The prototype's usability is also assessed. The findings indicate that using the ray tracing immersive learning environment results in a supplemental increase in understanding in users who have previously learned ray tracing using conventional means.

This study examined the visual design processes and strategies used by design experts and non-design college students when composing an infographic. All participants created an infographic on a personal computer and were asked to think aloud as they performed the task. The goal was to identify differences in the strategies utilised to produce higher and lower-quality infographics scored across 17 design criteria. Results revealed six design processes: (1) create structure and grid, (2) establish visual hierarchy, (3) define visual rules, (4) replicate visual rules, (5) test and adjust, and (6) validate and revise. High-rated infographics were produced using a more systematic process, starting with working on the structure and grid and establishing a visual hierarchy, and moving on to define and replicate visual rules. Design strategies from the comparative analysis included: (1) laying out the elements over a grid and working on visual hierarchy before working on details, (2) placing related content near each other and less related content spaced apart, (3) using up to two font styles and opting for legible over decorative fonts, (4) testing various colours, fonts, and graphics while preserving the overall structure and hierarchy, and (5) stepping back to validate the overall design and making adjustments based on the optical weight. These processes and strategies were encapsulated into a five-stage Infographic Visual Design Model.

The purpose of this paper is to examine how infographics are used in the dynamics of designing or creating in the teaching and learning process. Utilising a bibliometric approach and content analysis, we examined a sample of 760 documents from the Web of Science and Scopus databases with no lower time limit until November 2023. The analyses aimed to identify trends, including main topics, authors, sources, most cited articles, institutional affiliations, and countries in the literature. This bibliometric approach allows for the observation of trends in the educational application of promoting visual literacy through students' design or creation of infographics in formal and informal learning settings. Initial publications emerged in 2007, gaining momentum from 2014 to the present. The most prolific fields were medical science, chemistry, and computer science. This investigation shows that educational institutions could employ infographics beyond present boundaries to prepare students--particularly Generation Alpha, digital natives--for a data-driven society. Institutions should expand their use of infographics to improve visual literacy and address the changing educational requirements of students in a dynamic learning environment. Overall, this paper provides insights into the readiness of educators and institutions to engage Generation Alpha, the digital natives, through visual literacy and infographics.

Recent advances and applications of artificial intelligence (AI) have increased the opportunities for students to interact with AI in their learning tasks. Although various fields of scholarly research have investigated human-AI collaboration, the underlying processes of how students collaborate with AI in a student-AI teaming scenario have been scarcely investigated. To develop effective AI applications in education, it is necessary to understand differences in the student-AI interaction (SAI) process depending on students' characteristics. The present study attempts to fill this gap by exploring the differences in the SAI process amongst students with varying drawing proficiencies and attitudes towards AI in performing a public advertisement drawing task. Based on the empirical evidence obtained from the think-aloud protocols of 20 Korean undergraduate students, the study first conducted a lag sequential analysis to identify statistically significant linear patterns of each group and then chronologically incorporated them into the SAI duration via coded activity alignment series to distinguish the overall SAI process of each group. The study revealed the distinctive differences in SAI processes of students with different attitudes towards AI and drawing skills. To better facilitate student-AI teams for learning, a range of implications of educational AI development and instructional design is discussed.

Many academic teachers present data as static graphics in their lectures and courses. However, data structures have become more complex in the last decades, especially in the biomedical disciplines, and interactive graphics can provide a better means to communicate the scientific contents to students. Besides, the technological qualifications of academic staff are diverse, and it has been little studied how these teachers can be trained to program and implement interactive graphics for their courses. It is also little known whether interactive graphics will be helpful for teaching and learning. We conducted a pilot online workshop to identify aspects that need to be addressed when teaching academic staff to program interactive graphics in form of Shiny-apps based on the programing language R. The n = 25 participants were academic staff from the fields of medicine or natural sciences. Pre- and post-workshop questionnaires were used to identify which aspects should be considered in future workshops, to query the usefulness of interactive graphics for teachers and students, and to identify the impact of the workshop on the teacher's opinion towards digital teaching devices and their preparedness to program own interactive graphics. Most participants showed strong interest to use interactive graphics in their courses after the workshop, and interactive graphics were overall rated as very helpful for teachers and students. However, only those with prior programming knowledge intended to implement own graphics. We conclude that an extension of the workshop will be necessary to provide additional training for participants with no background in R programming.

Students' engagement in multimodal remediation of learning material in the form of slideshow presentations dominates universities. Yet, diversification of learning artifacts through the creation of more diverse types of multimodal content is scarce. The current article therefore proposes an innovative project during which students summarize research articles (RAs) by remediating their content into two increasingly popular communication formats: infographics and graphical abstracts (GAs). Following step-by-step activities that enhance student agency, learners self-regulate, work in groups, and learn to design these types of visuals. We discuss both modes and practices and present them visually in the format of instructional infographics, providing insights compiled in our own reflective journals as course facilitators. Courses: Professional Communication, Academic Communication, Science Communication, Technical Writing, Social Science Research Methods, English for Research Purposes, English for Specific Purposes, English for Academic Purposes, Visual Literacy, and Multimodality courses. The activities of multimodal remediation of academic texts into infographics and GAs may be adapted for all levels of students, including those who plan to continue with research activities in the future. Objectives: The proposed activities will help students to: (1) extract essential information from the RAs; (2) become acquainted with expert expectations regarding infographics and GAs (i.e. author guidelines in scientific journals); (3) critically evaluate the construction criteria of visuals for scholarly publication; (4) communicate research content (scientific data) visually by learning to design two popular formats for communicating research; (5) reflect on how effective multimodal construction is compared to the ones created by peers or the examples provided; (6) familiarize themselves with the target academic discourse; (7) foster learner agency, self-regulation, and autonomy; and (8) develop effective team working and collaboration subskills (e.g. responsibility sharing, taking into account the perspectives of others, etc.).

Currently, augmented reality (AR) is one of the emerging technologies which is being widely used in the education sector. In engineering drawing, AR has been implemented to enhance learners' spatial ability but not their conceptual knowledge yet. Therefore, this study aims to evaluate the effect of AR on engineering drawing students' learning performance. In this study, we developed an AR-based application EDINAR to learn engineering drawing concepts for undergraduate engineering students. The study included 392 first-year students from an engineering institution. The control group (N = 196) studied engineering drawing using traditional methods, whereas the experimental group (N = 196) used an AR-based engineering drawing application (EDINAR) to learn engineering drawing. One-way ANOVA was used to analyse the performances of both groups. The findings revealed that students studying engineering drawing with the help of EDINAR outperformed those using traditional approaches. In addition, we received positive feedback about the AR application from the experimental group about their learning experience. Based on these results, it is recommended to incorporate AR in engineering education to improve the learning performance and students' learning experience.

This paper aims to analyse to what extent the engineering curricula contribute to the development of visual literacy among engineering students. Communicating and thinking visually is a basic skill for all engineers, being a fundamental part of their educational stage. For this purpose, Engineering Graphics subjects from 30 engineering schools from Spain have been selected to review their content. The sample consists of 80 subjects of Engineering Graphics, mechanical design and computer-aided design. The curricula were analyzed using a quantitative and qualitative method. A database has been developed where keywords that identify the objectives of the analysis have been tabulated. Learning technical visual language and visualization skills as a means of developing visual literacy in engineering has been taken as the basis of the analysis. The results show that the curricula of the subjects contemplate the development of graphic skills around communication and technical representation and, to a lesser extent, visualization. On the other hand, the teaching activities contemplated do not dive into the cognitive aspects of graphics. We can also observe the pre-eminence of computer graphics as the main basis for teaching activities and marginal use of freehand drawing, which is basic for the development of Visual Literacy.

Analogical thinking is one of the thinking processes that is associated with creativity. This paper explores how it is experienced in Graphic Design elaborations using Computer Graphic Technology (CGT). Data are collected through concurrent and retrospective probing from three undergraduates and analysed through phenomenological reduction to identify the constituents and elements of the creative analogy's general psychological structure. The findings show that the general structure of the creative analogical experience is a relationship between three constituents namely: (1) the experience of recalling knowledge or information; (2) the use of knowledge for ideation; and (3) the use of knowledge to conclude ideas. The findings also show that the underlying elements of these constituents are conceptual (declarative) and technical (procedural) knowledge and its combinations that are consistent with the theories of analogical thinking. This article concludes with recommendations for future research and insights on its implementation in Design Education.

During the junior high and high school years, there is a dramatic decrease in motivation for math studies, which has been found to play a major role in learning processes. Many attempts have been made to mitigate this decrease in motivation and to encourage mathematics studies in higher grades. One way that researchers have proposed to stimulate students' curiosity and their perceived ability in math is to integrate technology into teaching. Such technology includes technological tools, digital educational activities, learning support software. Using tablet in class has significant potential to improve learning but the issue of how to effectively integrate digital technology into teaching and learning practices becomes critical. According to that knowledge we examined the impact of the use of a digital writing board (similar to tablet) by the lecturer during frontal lectures in mathematics on students' learning motivation in an engineering academic preparatory program, following motivational constructs: self-efficacy, implicit theory of ability, value beliefs, and learning climate. The results showed that the technological tool positively affected two important motivational constructs that influence general motivation for mathematics studies.

Objectives: The purpose of the study is to examine various dimensions of aesthetic visual design and their role in predicting usability in e-learning in higher education institutions of northern India. Using quantitative means of data collection, this research identified, ways and means to make learning content effectively usable, that is, attractive, interesting, motivating, and engaging for the learners. Method: A survey questionnaire was developed through focused group discussions with field experts. Data were collected through online as well as offline modes. A Google form was created and its weblink was shared with the students pursuing degree courses in various state universities in northern India. Several visits and revisits were also undertaken to various universities to approach the respondents. Results: Results confirmed consistency, typography, graphics, grid, and layout as factors responsible for predicting usability of e-learning. Surprisingly, color and compositional guidelines emerged insignificant. Implications: The study has implications for teaching and learning activities that promote effective learning. The findings are beneficial for course-design faculty who develop modules by considering visual design elements that can facilitate interaction with and understanding of content by students learning in an online modality.

The "new digital art? genre has emerged to describe various works of art that have evolved with the development of digital technologies. In its broadest sense, digital art encompasses everything from high-end machine learning applications to the use of interactive elements in traditional media. There is also an increase in the interaction between information technologies and art. Science, art and technology has been increasing and becoming widespread since the 60s, when scientists, artists and inventors began collaborating and using electronic devices to create art. The experience that results from consuming art and culture is multifaceted in nature. It can be individual or collective, physical or virtual, active or passive, public or private, on-site or in private places, open-air or indoor. With the spread of digital art, there is a remarkable increase in the commodification of art. This article, in this context, analyzed and discussed digital art, its positive and negative aspects, and the commodification of this art type on the basis of literature.

Image-text conversion for web-based drawing involves mental activities of reification which sometimes leads students fluent in graphical hand skills to find it difficult to learn program code drawing. 35 people completed experiments on Topics 1 and 2 and 30 people completed experiments on Topics 1 to 3 on webpage design. A pretest and posttest determined their learning style (visual or verbal), basic programming ability, and cognitive abilities (including logical reasoning, figural flexibility, and spatial perception--orientation and measurement). Statistical analyses and semi-structured interviews examined student performance. Students with different learning styles and different cognitive abilities displayed significant differences in the three topics. K-means clustering demonstrated the originality, aesthetic sophistication, and level of interaction to be critical yardsticks in measuring programming learning achievement. This research demonstrates factors that influence the learning of web-based drawing and offers new opportunities for understanding how front-end engineer novices can apply computational thinking skills to implement webpage design. Specifically, mental models may be integrated by graphical, heuristic, abstract, and sequential thinking in turn to solve problems in web-based drawing.

For students to gain the most out of education, they need to form long-term memories from experiences gained through active learning. The greatest distinction between active learning and traditional approaches involves the types of tasks and problems the students are challenged to solve. Active learning activities should be structured with student pairs to groups no larger than four participants, with one person in each group as the scribe or recorder and all others prepared to share ideas with their group members. There are variations of active learning formats such as Think-Pair-Share, Concept Test, and Think-Aloud Pair Problem Solving (TAPPS). In addition, there are several different approaches to get students to learn. Cooperative learning, collaborative learning, peer learning, and problem-based learning are a few of the formats educators could utilize in an engineering graphics course.

Computer simulation and animation (CSA) is educational technology in which computer programs are employed to simulate and animate real-world physical phenomena and processes. CSA has attracted growing attention and received an increasing number of applications in the international science, technology, engineering, and mathematics education community in recent years. The present study focuses on developing and assessing two CSA learning modules for improving student learning and problem-solving related to impulse and momentum in particle dynamics. Both CSA learning modules integrate mathematical problem-solving procedures into computer simulation and animation. They have interactive computer graphical user interfaces, which enable students to change input variables and visualize how output variables change accordingly. A quasi-experimental, quantitative research study was performed, involving 285 undergraduate engineering students divided into a comparison group that did not use CSA and an intervention group that used CSA. The results of statistical non-parametric analysis on the data collected from pre- and post-tests on the two groups show that, on average, the intervention group achieved more learning gains than the comparison group by 44% and 40% from two CSA learning modules, respectively. The difference in learning gains between the two groups of student participants was statistically significant.

The way medical students learn anatomy is constantly evolving. Nowadays, technologies such as tablets support established learning methods like drawing. In this study, the effect of drawing on a tablet on medical students' anatomy learning was investigated compared to drawing or summarizing on paper. The quality of drawings or summaries was assessed as a measure of the quality of strategy implementation. Learning outcome was measured with an anatomy test, both immediately afterward and after 4-6 weeks to assess its sustainability. There were no significant group differences in learning outcome at both measurement points. For all groups, there was a significant medium strength correlation between the quality of the drawings or summaries and the learning outcome (p < 0.05). Further analysis revealed that the quality of strategy implementation moderated outcomes in the delayed test: When poorly implemented, drawing on a tablet (M = 48.81) was associated with lower learning outcome than drawing on paper (M = 58.95); The latter (M = 58.89) was related to higher learning outcome than writing summaries (M = 45.59). In case of high-quality strategy implementation, drawing on a tablet (M = 60.98) outperformed drawing on paper (M = 52.67), which in turn was outperformed by writing summaries (M = 62.62). To conclude, drawing on a tablet serves as a viable alternative to paper-based methods for learning anatomy if students can make adequate use of this strategy. Future research needs to identify how to support student drawing, for instance, by offering scaffolds with adaptive feedback to enhance learning.

A person cultivates their creative skills influenced by various types of activities. The purpose of the work is to study the peculiarities of the development of students' creative thinking skills, which are interrelated with the development of appropriate stages of team teaching, as well as to determine the impact of creative thinking on the indicators of academic performance and motivation to learn. The authors used the methods of sociological survey, which allowed them to determine that the largest number of students had mastered the skills of discipline (27%) and emotionality (21%) to a greater extent at the initial stage of the study. The results showed that 11% of the students in creative subjects (painting, digital art) and 7% of students in general disciplines (history, sociology, pedagogy, mathematics, physics, Chinese, cultural studies) had their academic performance at a high level before the start of online learning. The process of online teaching to paint was based on teamwork using the technologies of online education through educational online platform in the context of digital art. The results of the survey showed that the students had developed their creative skills significantly after training. The development of creative manner (29%) and analytical thinking (28%) were most popular. The authors determined that 88% of the students had received high grades in creative disciplines and 83% of the students in general academic disciplines after training. Most students were characterized by a high level of knowledge. The results are valuable for researchers who study the relationship between the development of creative skills and knowledge in general academic subjects, as well as strive to develop new curricula.

Design and computer graphics curricula for tertiary education include 3-D modeling skills. Students must learn to represent (complex) 3-D objects by means of parametric surfaces or polygonal meshes. Three-dimensional modeling may be a complex task, and students must be able to accrue a certain deal of experience in the field before passing the exam. The main difficulties the students must face mainly concern the comprehension of 3-D shapes and the choice of the most appropriate modeling techniques. This article proposes a framework to support bachelor's degree students in modeling 3-D objects by means of parametric surfaces. The proposed framework provides two augmented reality (AR) apps for smartphones and a web portal. The mobile AR apps allow students to deeply visualize 3-D object shapes, thus performing a set of guided exercises to practice basic modeling techniques. On the other hand, the web portal allows students to share their models with teachers and classmates to obtain feedback and comments. The preliminary results show the effectiveness of the proposed solution, as all volunteers involved in the experimental phase achieved better results after using the tools. Moreover, the students' opinions about the proposed framework are positive.

Game-Based Learning (GBL) is increasingly widespread as a learning technique in the engineering studies. However, this innovative methodology may be difficult to incorporate in some subjects due to their complex contents. This paper aims at combining traditional learning methodologies with game mechanics by using an ad-hoc gaming web environment and mobile devices to analyse the academic performance and motivation in engineering studies. A comparative study was carried out with 96 first-year engineering students. In this experience, the students were randomly divided into two groups: Control Group (CG) and Experimental Group (EG). The first group made use of the traditional learning methodology used, whilst the second group combined the traditional methodology with GBL and Information and Communication Technologies (ICT). The obtained results show that EG students significantly improve their academic performance and motivation, expressing a succinctly greater interest in the studied subject. Therefore, the integration of GBL in the teaching methodology could have a very positive impact as well as it could greatly ease the teaching-learning process in engineering studies.

Realistic visualizations are abundantly used in digital education. However, the use of realism is still thought to risk a cognitive overload due to excessive details. Moreover, it is still not precisely known whether there is an optimal level of realism that benefits learners the most. In two experimental studies, different versions of anatomical visualizations were compared regarding their effects on retention performance and the subjective cognitive load experienced during learning. In Experiment 1 (n = 73), four visualizations with minor variations in the geometry and shading of the model featured in the visualizations were used. Although neither the level of detail in the geometry nor the realism of the shading resulted in significant differences, a detailed model with simplified shading elicited the highest retention scores descriptively. In Experiment 2 (n = 156), a schematic visualization was compared with an "idealized" model featuring only simplified shading and a highly realistic rendering. There most realistic version elicited the highest retention scores, but also the highest cognitive load ratings. Taken together, the results suggest that the optimal level of realism might lie on the more realistic end of the spectrum for learning tasks focused on the memorization of shapes that are assessed using image-based tests.

Contribution: Determine and analyze the gap between software practitioners' education outlined in the 2014 IEEE/ACM software engineering education knowledge (SEEK) and industrial needs pointed by Wikipedia articles referenced in Stack Overflow (SO) posts. Background: Previous work has uncovered deficiencies in the coverage of computer fundamentals, people skills, software processes, and human-computer interaction, suggesting rebalancing. Research Questions: 1) To what extent are developers' needs, in terms of Wikipedia articles referenced in SO posts, covered by the SEEK knowledge units? 2) How does the popularity of Wikipedia articles relate to their SEEK coverage? 3) What areas of computing knowledge can be better covered by the SEEK knowledge units? 4) Why are Wikipedia articles covered by the SEEK knowledge units cited on SO? Methodology: Wikipedia articles were systematically collected from SO posts. The most cited were manually mapped to the SEEK knowledge units, assessed according to their degree of coverage. Articles insufficiently covered by the SEEK were classified by hand using the 2012 ACM computing classification system (CCS). A sample of posts referencing sufficiently covered articles was manually analyzed. A survey was conducted on software practitioners to validate the study findings. Findings: SEEK appears to cover sufficiently computer science fundamentals, software design, and mathematical concepts, but less so areas, such as the World Wide Web, software engineering (SE) components, and computer graphics. Developers seek advice, best practices and explanations about software topics, and code review assistance. Future SEEK models and the computing education could dive deeper in information systems, design, testing, security, and soft skills.

In this study, the contribution of the 3D computer modeling to the twenty-first century's common competencies was evaluated from the perspective of secondary school students. The one-group post-test only design was used in the study. The instruments of the data collection process were an achievement test and a questionnaire developed by the researchers. The t-test and single sample chi-square test for related samples were performed to analyze the gathered data. The results of the study presented that secondary school students thought that 3D computer modeling education contributes to the lectures as mathematics, geometry, technological information, and design. Moreover, it supports the development of design, communication, collaboration, creativity, and problem-solving skills positively.

Computed-generated imagery (CGI) generates diverse views and perceptions of the past. These new experiences impact, directly or indirectly, the teaching and learning of history. This article presents didactic iconographic works on the Spanish Civil War created by the DIDPATRI (Didactics of Heritage and New Technologies) research group at the University of Barcelona. The didactic approach to this conflict reveals various problems that make it an interesting testing ground for new iconographies that contribute to an understanding of it. The proposal looks at the generation of "virtual" iconography to facilitate the teaching of content in formal and non-formal spaces. It is argued that CGI opens up possibilities to researchers, teachers, students, and technicians for the generation of comprehensive communication elements of history. The attractiveness of this new "virtual" iconography of the past lies in the possibility to create integrated ensembles where the facts, concepts, situations, and representations of materiality that the creators want to represent can appear. The resulting iconographic product can be applied for use in various environments, such as teaching, heritage, tourism, and cultural industries, and via different media, such as panels, apps, web, audio-visuals, museography, games, books, and notebooks.

Formal learning environments have struggled to introduce STEM content and STEM careers to students from underrepresented populations. This problem is exacerbated when dealing with students who live in rural areas where access to quality materials and instruction is limited. The eMentorship project is an innovative approach to mentoring that utilizes the latest in communication technology to help support a formal mentoring program. This study investigates the impact of a virtual mentorship program on underrepresented students living in rural North Carolina. The project was an eight-week mentoring program that matched underrepresented student teams with graduate student mentors from a local university. In addition to the mentoring experience student participants were also taught three-dimensional (3-D) modeling skills using a "flipped" classroom approach to instruction. The paper presents the curriculum developed to guide the program, student examples of 3-D models, self-efficacy scores and qualitative interviews conducted with the student participants. Results of the study provide evidence that students found great value in the mentoring experience and were able to learn 3-D modeling skills in a virtual learning environment.

With the increase in online course use (Allen & Seaman, 2017), there is an increasing need to determine the most effective (i.e., the most conducive for learning) way to present lectures online (e.g., video lectures). Lecture graphics that are interesting but extraneous to the content (e.g., a celebrity), have been shown to impair comprehension of the material, likely resulting from an increase in cognitive load. In this study, the use of graphics on the slides of an online psychology lecture was manipulated to determine the extent to which images can improve (or impair) comprehension as well as the effect it may have on intentional and unintentional mind-wandering. Across our two experiments, we demonstrate no differences across conditions (i.e., unnecessary graphics, relevant graphics, no graphics) in overall comprehension and limited differences in mind wandering behavior.

This study explores the dynamic, interactive nature of digital drawings and writing in a knowledge building community in which students used a multimedia online environment--Knowledge Forum--to represent and advance ideas in the field of optics. The research employs a mixed-methods case study to collect and analyze multimedia notes created by 22 fourth-grade students. Graphical notes--notes containing drawings--included more idea units and more sophisticated ideas than non-graphical notes. Quality of drawing also correlated with idea improvement in Knowledge Forum notes, with ratings of idea improvement based on conceptual understanding of optics. Overall, findings revealed significant advantages of online drawing for Grade 4 students, with case-study analysis revealing the many ways in which graphics complement writing and contribute to knowledge building.

In many science and engineering undergraduate programmes, physics courses are fundamental and can be seen as a potential place where students can develop complementary abilities such as the computational thinking process. The present work proposes and describes the learning science and engineering with electronic spreadsheets cycle (LSEESC) methodology to improve the learning of concepts in physics, science, and engineering, with the use of electronic spreadsheets as a digital and supported learning tool, promoting the understanding, critical thinking, and reasoning of physics in students based on activities such as the programming of all dynamical systems, describing mathematical evolution, generating and analysing graphics, and explaining physical phenomena with a high comprehension and transfer of knowledge to identify where the concept can be applied in their professional context using real-life examples or simulations. The proposed methodology can be implemented in different learning scenarios; that is, if the class uses computational devices or if the teacher exposes a specific topic in the classroom, physics and mathematics can be exposed to feedback from students in a comprehensible manner at any time during the instruction, after which a new sequence (cycle) based on previous results can be ejected and adapted. To describe the LSEESC methodology, we use the rigid body concept, which is one of the most general concepts in science and engineering and, integrates the majority of the fundamentals in mechanics, such as kinematics, forces, dynamics, and circular movement. This can be described as the concept of viewing all related equations and plotting the results with the relationships between all variables. The methodology uses simulations or real-life examples to reinforce the concept viewed, allowing students to see, in an integrated manner, how the same variables and concepts can be seen and interact in a real scenario for their professional context.

Prior research has indicated that consumers' decisions are significantly influenced by online reviews. However, existing research has focused mainly on attributes (e.g., average ratings) that are not fully controlled by firms; only limited research has investigated how controllable attributes (e.g., review display formats) affect consumers. Drawing on visual perception research, the authors examine the effectiveness of two prominent graphical display formats used by major e-commerce platforms: one that displays rating distributions in a proportional format (e.g., Amazon) and one that does so in a simple format (e.g., Google). The results indicate that due to the changes in graphs' reference points caused by the shrunken x-axis in simple bar graphs, consumers respond more positively to an item when its rating distribution is displayed in a graphically simple (vs. proportional) format. This effect is moderated by the distribution's peak value (i.e., the share of the most frequent rating) and imbalance score (i.e., the difference between the share of positive and negative ratings). Furthermore, even an item's future ratings are influenced by the graphical format in which its prior ratings are displayed. The contributions to the marketing literature are discussed, and insights that can aid managers in making more informed decisions are provided. [ABSTRACT FROM AUTHOR]

Digital heritage portal interfaces are generally similar to digital library and search engine interfaces in displaying search results as a list of brief metadata records. The knowledge organization and search result display of these systems are item-centric, with little support for identifying relationships between items. This paper proposes a knowledge graph system and visualization interface as a promising solution for digital heritage systems to support users in browsing related items, understanding the relationships between items, and synthesizing a narrative on an issue. The paper discusses design issues for the knowledge graph, graph database, and graph visualization, and offers recommendations based on the authors' experience in developing three knowledge graph systems for archive and digital humanities resources: the Zubir Said personal archive collection at the Nanyang Academy of Fine Arts, Singapore; Singapore Pioneers social network; and Polyglot Medicine knowledge graph of Asian traditional and herbal medicine. Lessons learned from a small user study are incorporated in the discussion. [ABSTRACT FROM AUTHOR]

Spherical harmonics provide a smooth, orthogonal, and symmetry-adapted basis to expand functions on a sphere, and they are used routinely in physical and theoretical chemistry as well as in different fields of science and technology, from geology and atmospheric sciences to signal processing and computer graphics. More recently, they have become a key component of rotationally equivariant models in geometric machine learning, including applications to atomic-scale modeling of molecules and materials. We present an elegant and efficient algorithm for the evaluation of the real-valued spherical harmonics. Our construction features many of the desirable properties of existing schemes and allows us to compute Cartesian derivatives in a numerically stable and computationally efficient manner. To facilitate usage, we implement this algorithm in sphericart, a fast C++ library that also provides C bindings, a Python API, and a PyTorch implementation that includes a GPU kernel. [ABSTRACT FROM AUTHOR]

Due to the evolution of graphics processors over recent decades it has now become possible to produce high-quality, realistic three-dimensional scenes. However, aliasing occurs during the sampling process performed during rasterization, which causes a serrated effect around the edges of the objects presented in the scene, highlighting an unreal aspect of the image and causing displeasure to the viewer. This paper aims to develop an anti-aliasing treatment based on rotated spatial filtering. It undertakes edge detection by applying spatial filtering with a simple linear regression technique. A smoothing spatial filter is then rotated to match the direction of the inspected edge and is applied to the affected regions. Testing was performed on an OpenGL application, processing the rendered image from the framebuffer, and Blender, a 3D modeling software that enables scenes with more complex graphics. The results have demonstrated the effectiveness of the proposed method in smoothing aliasing with good quality while preserving the details of the scene. Hence, the problem was managed effectively with a post-filtering approach and without oversampling. The running time of the algorithm is O(n), and the memory used is O(n). [ABSTRACT FROM AUTHOR]

This paper presents an efficient algorithm for voxelizing the surface of triangular meshes in a single compute pass. The algorithm uses parallel equidistant lines to traverse the interior of triangles, minimizing costly memory operations and avoiding visiting the same voxels multiple times. By detecting and visiting only the voxels in each line operation, the proposed method achieves better performance results. This method incorporates a gap detection step, targeting areas where scanline‐based voxelization methods might fail. By selectively addressing these gaps, our method attains superior performance outcomes. Additionally, the algorithm is written entirely in a single compute GLSL shader, which makes it highly portable and vendor independent. Its simplicity also makes it easy to adapt and extend for various applications. The paper compares the results of this algorithm with other modern methods, comprehensibly comparing the time performance and resources used. Additionally, we introduce a novel metric, the ‘Slope Consistency Value’, which quantifies triangle orientation's impact on voxelization accuracy for scanline‐based approaches. The results show that the proposed solution outperforms existing, modern ones and obtains better results, especially in densely populated scenes with homogeneous triangle sizes and at higher resolutions. [ABSTRACT FROM AUTHOR]

The texture mapping technique based on irregular surfaces is widely used in many fields such as film and television, industry and games, etc. In order to adapt to the rapid development in the field of computer graphics and further enhance the uniformity and effectiveness of the texture mapping effect, a triangular mesh simplified texture mapping technique based on the optimized spring-fingertip is proposed. Firstly, a complex two-dimensional graph is established through the spring-fingertip model, which is parameterized and normalized to reduce the deformation of the texture; subsequently, the concept of triangular mesh simplification is introduced to optimize the model timeliness, which replaces the traditional way of folding the edges; finally, the weight of each edge is further analyzed through local curvature calculation. In order to verify the effectiveness of the texture mapping method, simulation and analysis experiments are done, and the experimental results show that the accuracy of the model reaches 99.25%, which is an average improvement of 7.19% relative to the remaining four models. Therefore, the texture mapping model based on optimized triangular mesh effectively improves the realism of the mapping effect and reduces the computational burden of the model. [ABSTRACT FROM AUTHOR]

Background: Infographics facilitate rapid information dissemination with enriched eye‐catching content on social media, but it is unclear what factors affect the adoption of information presented in this way. Objectives: We tested whether the Information Acceptance Model applies to infographics on healthy lifestyle and fitness topics. Methods: Two hundred and four university students were invited to participate in an online survey on their acceptance after reading some healthy lifestyle and fitness topics infographics shared on social media. The data collected were analysed using Partial Least Square path modelling. Results: The results confirmed information usefulness as a predictor of information adoption; attitude towards information and information adoption were the predictors of behavioural intention. Information credibility and attitude towards information, but not information quality and needs, were significantly related to information usefulness. Social media usage and education level were factors affecting infographics impressions. Discussion: Results support most hypotheses. It confirms information usefulness as a predictor of infographics adoption. Attitudes towards information and information adoption are predictors of behavioural intentions of following healthy lifestyle and fitness suggestions through social media infographics. Conclusion: Social media facilitates interpersonal communication, information exchange and knowledge sharing, and infographics may draw people into healthy lifestyle and fitness information items relevant to them. [ABSTRACT FROM AUTHOR]

Terrain visibility analysis is vital in geospatial research, employing computer geometry and graphics principles for computing and visualizing visibility between observation and target points. The observation point setup problem is crucial for tasks like sentry point selection and signal base station placement. This problem involves choosing the minimum viewpoints on terrain for optimal joint view coverage, presenting a combinatorial optimization challenge. As technology advances, data can be acquired with increasing precision, the number of viewpoints that can be extracted from the same area is gradually increasing as well, obtaining candidate viewpoints and determining optimal combinations become challenging. This paper proposes a novel method, Stepwise Maximum Viewshed (SMV), addressing observation point setup by stepwise filtering the maximum viewshed and can customize the size of the observation point combination. In complex mountainous terrain, the SMV algorithm demonstrates superior joint view coverage compared to Candidate Viewpoints Filtering (CVF) and Simulated Annealing (SA) algorithms. Experimental results reveal up to 5.59% improvement over CVF and a maximum of 12.52% over SA in joint viewshed coverage. [ABSTRACT FROM AUTHOR]

Edge-aware image smoothing refers to the removal of details with edges preserved. It is an essential topic in the field of image processing and computer graphics. In this paper, in order to achieve better edge preservation than the existing models, we propose a robust edge-preserving image filtering method based on a complementary weighting scheme. Both isotropic and anisotropic weights are involved in our model to adapt the fidelity and the regularization terms. To efficiently solve the proposed model, we introduce an effective algorithm based on additive half quadratic minimization, alternating direction of multipliers, and Fourier domain optimization strategies. We experimentally validate the proposed filter on several low-level vision tasks. Both quantitative and qualitative experimental results show significant superiority of our proposed filter compared to existing techniques. Furthermore, the filter exhibits high efficiency and is able to process 720P color images (over 10 fps) in real-time on an NVIDIA RTX 3070. Therefore, it is practical for real-world applications. [ABSTRACT FROM AUTHOR]

This article explores various techniques for generating fractal-like Bézier curves in both 2D and 3D environments. It delves into methods such as subdivision schemes, Iterated Function System (IFS) theory, perturbation of Bézier curves, and perturbation of Bézier basis functions. The article outlines conditions on subdivision matrices necessary for convergence and demonstrates their use in creating an IFS with an attractor aligned to the convergent point of the subdivision scheme based on specified initial data. Additionally, it discusses conditions for obtaining a one-sided approximation of a given Bézier curve through perturbation. The article also addresses considerations for perturbed Bézier basis functions to construct fractal-like Bézier curves that remain within the convex hull polygon/polyhedron defined by control points. These methods find applications in various fields, including computer graphics, art, and design. [ABSTRACT FROM AUTHOR]

Summary: Traditional post‐earthquake inspection of civil infrastructure is conducted manually, taking a considerable amount of time and often putting inspectors in harm's way. This problem is exacerbated in modern cities, where millions of people can be left homeless until their residences are deemed safe to reinhabit. Image collection enabled by commercial unmanned aerial vehicles (UAVs) combined with computer vision‐based techniques has provided an alternative with high potential for rapid post‐earthquake inspection. However, the extracted images of the damage alone are inadequate to evaluate the system‐level safety condition of a structure. The quality of the visual information also heavily relies on the effectiveness of the UAV inspection scheme which is susceptible to environmental uncertainties. To this end, a graphics‐based digital twin (GBDT) framework is developed for UAV‐aided post‐earthquake inspection of high‐rise buildings and validated using a high‐rise building in Guangzhou, China. The GBDT is comprised of a finite element (FE) model and a photorealistic computer graphics (CG) model, with the latter being informed by the former, jointly providing as a comprehensive virtual representation of the structure so that every step of the post‐earthquake inspection procedure can be planned and evaluated virtually. First, to avoid the cumbersome nature of constructing the graphical representation of the numerous components in high‐rise buildings, the CG model in the GBDT is created by automatically importing structural components from the FE model and adding nonstructural components according to the dimensions of the as‐built structure. This fast modeling process as well as the accuracy of the virtual presentation are validated by point cloud comparisons between the CG model and the as‐built structure. Subsequently, the GBDT is used to showcase the evaluation of UAV flight schemes for post‐earthquake inspection of high‐rise buildings. To shorten flight time and place more emphasis on potential damage, FE analysis is conducted to determine the earthquake‐induced damage locations. Consistent damage hotspots are then marked on the CG model, along with restrictions from the real environment such as obstacles, weak satellite signal, wind speed, and lighting conditions considered in the synthetic environment. Finally, applying the synthetic environment as the testbed, three UAV‐aided inspection schemes are implemented virtually and the best UAV flight scheme is determined for the assumed field inspection. This example demonstrates the flexibility of the GBDT in representing the real‐world structure and environmental conditions and its efficacy in assisting decision making for rapid and effective structural inspection in the aftermath of an earthquake. [ABSTRACT FROM AUTHOR]

In approximation theory, classical discrete operators, like generalized sampling, Szász‐Mirak'jan, Baskakov, and Bernstein operators, have been extensively studied for scalar functions. In this paper, we look at the approximation of curves by a class of discrete operators, and we exhibit graphical examples concerning several cases. The topic has useful implications about the computer graphics and the image processing: We discuss applications on the approximation and the reconstruction of curves in images. [ABSTRACT FROM AUTHOR]

Background: The use of 3D imaging techniques, such as X-ray CT, in root phenotyping has become more widespread in recent years. However, due to the complexity of the root structure, analyzing the resulting 3D volumes to obtain detailed architectural root traits remains a challenging computational problem. When it comes to image-based phenotyping of excavated maize root crowns, two types of root features that are notably missing from existing methods are the whorls and soil line. Whorls refer to the distinct areas located at the base of each stem node from which roots sprout in a circular pattern (Liu S, Barrow CS, Hanlon M, Lynch JP, Bucksch A. Dirt/3D: 3D root phenotyping for field-grown maize (zea mays). Plant Physiol. 2021;187(2):739–57. https://doi.org/10.1093/plphys/kiab311.). The soil line is where the root stem meets the ground. Knowledge of these features would give biologists deeper insights into the root system architecture (RSA) and the below- and above-ground root properties. Results: We developed TopoRoot+, a computational pipeline that produces architectural traits from 3D X-ray CT volumes of excavated maize root crowns. Building upon the TopoRoot software (Zeng D, Li M, Jiang N, Ju Y, Schreiber H, Chambers E, et al. Toporoot: A method for computing hierarchy and fine-grained traits of maize roots from 3D imaging. Plant Methods. 2021;17(1). https://doi.org/10.1186/s13007-021-00829-z.) for computing fine-grained root traits, TopoRoot + adds the capability to detect whorls, identify nodal roots at each whorl, and compute the soil line location. The new algorithms in TopoRoot + offer an additional set of fine-grained traits beyond those provided by TopoRoot. The addition includes internode distances, root traits at every hierarchy level associated with a whorl, and root traits specific to above or below the ground. TopoRoot + is validated on a diverse collection of field-grown maize root crowns consisting of nine genotypes and spanning across three years. TopoRoot + runs in minutes for a typical volume size of on a desktop workstation. Our software and test dataset are freely distributed on Github. Conclusions: TopoRoot + advances the state-of-the-art in image-based phenotyping of excavated maize root crowns by offering more detailed architectural traits related to whorls and soil lines. The efficiency of TopoRoot + makes it well-suited for high-throughput image-based root phenotyping. [ABSTRACT FROM AUTHOR]

This study evaluates the effectiveness of fine‐tuning a semantic segmentation model to identify and quantify dollar spot in turfgrasses, the most extensively managed and researched disease of turfgrasses worldwide. Using the DeepLabV3+ model, recognized for its capability to segment complex shapes and integrate multi‐scale contextual information, the research leveraged a diverse dataset comprising various turfgrass species, disease stages, and lighting conditions to ensure robust model training. The trained model is able to identify and segment disease instances accurately and precisely, and the results indicate the potential for model‐based assessment to outperform traditional visual assessment methods in speed, accuracy, and consistency. The development of deep learning models on extensive datasets like ImageNet requires significant computational resources. However, by fine‐tuning a pretrained semantic segmentation model, we adapted it for disease segmentation using only a standard personal computer's graphics processing unit. This approach not only conserves resources but also highlights the practicality of deploying advanced deep learning applications in turfgrass pathology with limited computational capacity. The proposed model provides a new tool for turfgrass researchers and professionals to rapidly and accurately quantify this important disease under real‐world growing conditions. Additionally, the findings suggest the potential to apply deep learning algorithms to other turfgrass diseases to support data‐driven decisions. This could enhance disease management practices and improve decision‐making processes for fungicidal treatments, thereby improving the economic and environmental sustainability of turfgrass management. [ABSTRACT FROM AUTHOR]

Summary: Cracks can develop in high‐rise buildings because of long‐term environmental changes and extreme loading events such as strong winds or earthquakes. Although deep learning‐based identification methods can efficiently identify cracks, the accuracy of crack identification in high‐rise buildings needs to be improved due to the lack of crack datasets specifically related to high‐rise structures. Moreover, the number of available images of cracks in high‐rise is limited. To this end, this paper establishes an intelligent crack identification method based on a photorealistic synthetic modeling technique. First, a computer graphics (CG) model of a high‐rise building with assumed damage is constructed. Subsequently, the CG model is utilized to generate a dataset that includes photorealistic images of the high‐rise building as well as corresponding labels for various components and types of damage. The generated dataset is then used to train a DeepLabv3 + neural network for structural component and damage identification, followed by validation by employing images of both synthetic and full‐scale high‐rise buildings. The trained network can accurately identify different components in images of the full‐scale, high‐rise building and identify cracks that are intentionally synthesized in those images. The results show that the synthetic dataset generated by the CG model not only allows for fast and efficient labeling for the purpose of neural network training but also outperforms methods that do not consider any application‐specific context in crack identification. [ABSTRACT FROM AUTHOR]

This study reports an effective and robust edge-based scheme for the reconstruction of 3D human faces from input of single images, addressing drawbacks of existing methods in case of large face pose angles or noisy input images. Accurate 3D face reconstruction from 2D images is important, as it can enable a wide range of applications, such as face recognition, animations, games and AR/VR systems. Edge features extracted from 2D images contain wealthy and robust 3D geometric information, which were used together with landmarks for face reconstruction purpose. However, the accurate reconstruction of 3D faces from contour features is a challenging task, since traditional edge or contour detection algorithms introduce a great deal of noise, which would adversely affect the reconstruction. This paper reports on the use of a hard-blended face contour feature from a neural network and a Canny edge extractor for face reconstruction. The quantitative results indicate that our method achieves a notable improvement in face reconstruction with a Euclidean distance error of 1.64 mm and a normal vector distance error of 1.27 mm when compared to the ground truth, outperforming both traditional and other deep learning-based methods. These metrics show particularly significant advancements, especially in face shape reconstruction under large pose angles. The method also achieved higher accuracy and robustness on in-the-wild images under conditions of blurring, makeup, occlusion and poor illumination. [ABSTRACT FROM AUTHOR]

Real-time hybrid simulation has gained popularity over the last 20 years as a viable and cost-effective method of testing dynamic systems that cannot be tested using traditional methods. The emergence of multi-axial Real-time Hybrid Simulation (maRTHS) has led to an increase in the allowable fidelity of the numerical and experimental substructures. The testing community can now replicate multiple-degree-of-freedom (MDOF) responses of both substructures and thus can perform more representative tests. However, with this increased fidelity of the substructures comes an increased complexity of controlling these components. Specifically, multi-axial hydraulic actuator assemblages require nonlinear coordinate transformations to derive plant displacements as the force transducers on the actuators are not capable of performing this task directly. Recently, benchmark problems have been provided to the RTHS community in the form of virtual simulations. Virtual simulation refers to a fully virtual testing methodology where numerical and physical components are represented virtually. This approach enables the RTHS community to evaluate various control algorithms without the need to recreate physical components. This project aims to demonstrate the capability of computer vision-based displacement tracking in a realistic virtual simulation of the experimental substructure in avoiding excess nonlinear coordinate transforms. The tracking algorithm utilizing the Lucas-Kanade optical flow method is tested in the virtual simulation environment which is set up using real-time 3D creation engine, Unreal Engine 4 (UE4), and computer graphics software, Blender. This environment interfaces with MATLAB/Simulink, more specifically "Simulation Tool for v-maRTHS benchmark" developed for multi-axial tests. The result of this study establishes a novel framework for applying computer vision-based tracking algorithms and sensing in v-maRTHS simulations using simulated cameras within virtual simulation environments. A computer vision displacement tracking algorithm is developed and optimized to work in tandem with a MIMO PI controller to reduce tracking time delays within 31.25 milliseconds while tracking the nodal displacement and rotation of the frame within a normalized RMSE of 1.24 and 1.10 respectively. [ABSTRACT FROM AUTHOR]

A parameterization of a triangle mesh is a realization in the plane so that all triangles have positive signed area. Triangle mesh parameterizations are commonly computed by minimizing a distortion energy, measuring the distortions of the triangles as they are mapped into the parameter domain. It is assumed that the triangulation is fixed and the triangles are mapped affinely. We consider a more general setup and additionally optimize among the intrinsic triangulations of the piecewise linear input geometry. This means the distortion energy is computed for the same geometry, yet the space of possible parameterizations is enlarged. For minimizing the distortion energy, we suggest alternating between varying the parameter locations of the vertices and intrinsic flipping. We show that this process improves the mapping for different distortion energies at moderate additional cost. We also find intrinsic triangulations that are better starting points for the optimization of positions, offering a compromise between the full optimization approach and exploiting the additional freedom of intrinsic triangulations. [ABSTRACT FROM AUTHOR]